BE 8: Emotions

Neoclassical economics puzzle: Emotions are un-measurable

Effect of emotions is unpredictable (self-control/ projection bias/ social preferences) + therefore unmodelable

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Decision making under emotions: Model

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Decision making under emotions: Effort costs

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Decision making under emotions: Model (simplified)

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Decision making under emotions: Model predictions (1)

Willpower depletion or unrelated cognitive demands increases make it less likely that the individuals chooses Deliberative optimum (vice versa)

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Decision making under emotions: Model predictions (2)

If intensity for affective motivation increases (temporal/ non-temporal factors) affective preference for Affective optimum over Deliberative optimum, then affective intensity makes it less likely to choose deliberative optimum (vice versa)

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Model applications: emotions & intertemporal choice: model

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Model applications: emotions & intertemporal choice: model (simplified)

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Model applications: emotions & intertemporal choice: predictions (1)

Increasing the cost function = more myopic behaviour (present bias)

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Model applications: emotions & intertemporal choice: predictions (2)

Any factor that increases intensity of affective motivation for immediate payoff = more myopic behaviour

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Model applications: emotions & intertemporal choice empirics: time preference + mood (experiment)

ST mood manipulation through comedy clip/ asked questions about (mood/ time preference for indifference in $X/ demographic + psychological characteristics)

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Model applications: emotions & intertemporal choice empirics: time preference + mood (results)

Watching a comedy clid increases your NPV (discounting less) (predictions (1)) / Other expl: happiness makes you care less about money (prediction 2) / happiness makes you less risk averse about receiving money in future

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Model applications: emotions & intertemporal choice empirics: time preference + mood (ISSUES)

Reverse causality (people that have LT goals are happier) = Mood manipulation (ST comedy clip) = People dont tell truth = Pick one individual to actually receive $X

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Model applications: emotions & risk decisions (P.T): model

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Model applications: emotions & risk decisions (P.T): predictions (1)

Increase cost function = magnifies Prospect Theory (Loss Aversion/ Non-Linear decision weights)

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Model applications: emotions & risk decisions (P.T): predictions (2)

Lotteries with same good (money) + affective motivation intensity: increase in affective intensity = magnifies Prospect Theory

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Model applications: emotions & risk decisions (P.T) empirics: Sexual arousal & willpower depletion

When treated with sexual arousal = higher willingness to engage in **** behaviour/ risky behaviour (prediction 1)/ Other expl: sexual arousal may affect 1) Beliefs 2) Present bias 3) Honesty

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Model applications: emotions & social preferences: model

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Model applications: emotions & social preferences: model (simplified)

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Model applications: emotions & social preferences: Predictions (1)

Increase cost function = increases your care for others when affective motivation is high (vice versa)

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Model applications: emotions & social preferences: Predictions (2)

Any factor increasing affective motivation = increases your care for others (factor their utility into your utility much more)

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Model applications: emotions & social preferences empirics: NFL defeats + IPV (relation to the model)

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Model applications: emotions & social preferences empirics: NFL defeats + IPV (regression)

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Model applications: emotions & social preferences empirics: NFL defeats + IPV (results)

1) Upset losses = +ve coef (sig) 2) close losses = +ve coef (n.s) 3) upset win = 0

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Model applications: emotions & social preferences empirics: NFL defeats + IPV (ISSUES)

Selection = excuse to engage in IPV if watching NFL team loss = control for predicted outcomes

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Get Revising

BE 8: Emotions

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